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Errors and residuals
Results: 1777

#	Item
71	Communication-Efficient Online Detection of Network-Wide Anomalies Ling Huang∗ XuanLong Nguyen∗ Minos Garofalakis† Joseph M. Hellerstein∗ Michael I. Jordan∗ Anthony D. Joseph∗ Nina Taft† ∗ UC Berkeley † Add to Reading List Source URL: dept.stat.lsa.umich.edu Language: English - Date: 2007-02-27 15:27:27 Statistics Algebra Error Hypothesis testing Design of experiments Multivariate statistics Measurement Principal component analysis Anomaly detection Eigenvalues and eigenvectors Type I and type II errors Errors and residuals
72	PDF Document Add to Reading List Source URL: www.spc.ncep.noaa.gov Language: English - Date: 2015-12-09 05:46:40 Regression analysis Climate modeling Atmospheric model Errors and residuals Meteorology Derivative Truncation error Radiosonde Contour line
73	American Community SurveyTechnical Document ACS Overview Add to Reading List Source URL: www.higheredinfo.org Language: English - Date: 2012-05-01 08:34:11 Statistics Measurement Knowledge Error Sampling Estimation theory Robust statistics Margin of error American Community Survey Standard error Median Errors and residuals
74	c o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e ) 83–93 journal homepage: www.intl.elsevierhealth.com/journals/cmpb A diagnostic tool for population models using non-compa Add to Reading List Source URL: uu.diva-portal.org Language: English - Date: 2016-04-28 04:28:47 Summary statistics Econometrics Measurement Statistical theory Robust statistics Standard deviation Data analysis Regression analysis Deviation Statistics Errors and residuals Confidence interval
75	Administrative Notes StatisticsLecture 22 •  Homework 6 due in recitation tomorrow Inference for relationships Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2016-04-06 13:56:31 Statistics Parametric statistics Statistical inference Estimation theory Regression analysis Single-equation methods Linear regression Simple linear regression T-statistic Confidence interval Least squares Errors and residuals
76	Administrative Notes StatisticsLecture 27 •  Final Exam is Tuesday, May 10th (3-5pm) •  Covers Chapters 1-8 and 10 in textbook Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2016-04-25 15:34:36 Statistics Regression analysis Parametric statistics Probability distributions Statistical theory Measurement Central limit theorem Normal distribution Sampling distribution T-statistic Errors and residuals Linear regression
77	HW5 Solutions 1 IPSpoints] Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2016-03-28 11:36:59 Statistics Statistical inference Measurement Probability distributions Regression analysis Statistical theory Confidence interval Normal distribution Standard deviation Errors and residuals Statistical hypothesis testing
78	Administrative Notes StatisticsLecture 16 •  Homework 4 is due in recitation on Friday, March 18 Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2016-03-16 14:58:28 Statistical theory Measurement Normal distribution Statistical inference Regression analysis Standard error Standard deviation Errors and residuals T-statistic Sample size determination Central limit theorem Sampling distribution
79	Automated Algorithmic Error Resilience for Structured Grid Problems based on Outlier Detec;on Amoghavarsha Suresh and John Sartori University of Add to Reading List Source URL: cgo.org Language: English - Date: 2014-02-26 13:50:33 Statistics Robust statistics Statistical theory Regression analysis Error Outlier Statistical analysis Resilience Errors and residuals Psychological resilience
80	Alternating Minimization for Regression Problems with Vector-valued Outputs Prateek Jain Microsoft Research, INDIA Add to Reading List Source URL: dept.stat.lsa.umich.edu Language: English - Date: 2015-11-02 15:34:37 Regression analysis Estimation theory Covariance and correlation Parametric statistics Statistical theory Linear regression Estimation of covariance matrices Ordinary least squares Normal distribution Maximum likelihood estimation Covariance Errors and residuals

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